Hyaluronic acid stimulation of stem cells for cardiac repair: a cell-free strategy for myocardial infarct.

BACKGROUND: Myocardial infarction (MI), a representative form of ischemic heart disease, remains a huge burden worldwide. This study aimed to explore whether extracellular vesicles (EVs) secreted from hyaluronic acid (HA)-primed induced mesenchymal stem cells (HA-iMSC-EVs) could enhance the cardiac repair after MI. RESULTS: HA-iMSC-EVs showed typical characteristics for EVs such as morphology, size, and marker proteins expression. Compared with iMSC-EVs, HA-iMSC-EVs showed enhanced tube formation and survival against oxidative stress in endothelial cells, while reduced reactive oxygen species (ROS) generation in cardiomyocytes. In THP-1 macrophages, both types of EVs markedly reduced the expression of pro-inflammatory signaling players, whereas HA-iMSC-EVs were more potent in augmenting anti-inflammatory markers. A significant decrease of inflammasome proteins was observed in HA-iMSC-EV-treated THP-1. Further, phospho-SMAD2 as well as fibrosis markers in TGF-ß1-stimulated cardiomyocytes were reduced in HA-iMSC-EVs treatment. Proteomic data showed that HA-iMSC-EVs were enriched with multiple pathways including immunity, extracellular matrix organization, angiogenesis, and cell cycle. The localization of HA-iMSC-EVs in myocardium was confirmed after delivery by either intravenous or intramyocardial route, with the latter increased intensity. Echocardiography revealed that intramyocardial HA-iMSC-EVs injections improved cardiac function and reduced adverse cardiac remodeling and necrotic size in MI heart. Histologically, MI hearts receiving HA-iMSC-EVs had increased capillary density and viable myocardium, while showed reduced fibrosis. CONCLUSIONS: Our results suggest that HA-iMSC-EVs improve cardiac function by augmenting vessel growth, while reducing ROS generation, inflammation, and fibrosis in MI heart.

Cryo-electron microscopy-based drug design.

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Comprehensive Assessment and Early Prediction of Gross Motor Performance in Toddlers With Graph Convolutional Networks-Based Deep Learning: Development and Validation Study.

BACKGROUND: Accurate and timely assessment of children's developmental status is crucial for early diagnosis and intervention. More accurate and automated developmental assessments are essential due to the lack of trained health care providers and imprecise parental reporting. In various areas of development, gross motor development in toddlers is known to be predictive of subsequent childhood developments. OBJECTIVE: The purpose of this study was to develop a model to assess gross motor behavior and integrate the results to determine the overall gross motor status of toddlers. This study also aimed to identify behaviors that are important in the assessment of overall gross motor skills and detect critical moments and important body parts for the assessment of each behavior. METHODS: We used behavioral videos of toddlers aged 18-35 months. To assess gross motor development, we selected 4 behaviors (climb up the stairs, go down the stairs, throw the ball, and stand on 1 foot) that have been validated with the Korean Developmental Screening Test for Infants and Children. In the child behavior videos, we estimated each child's position as a bounding box and extracted human keypoints within the box. In the first stage, the videos with the extracted human keypoints of each behavior were evaluated separately using a graph convolutional networks (GCN)-based algorithm. The probability values obtained for each label in the first-stage model were used as input for the second-stage model, the extreme gradient boosting (XGBoost) algorithm, to predict the overall gross motor status. For interpretability, we used gradient-weighted class activation mapping (Grad-CAM) to identify important moments and relevant body parts during the movements. The Shapley additive explanations method was used for the assessment of variable importance, to determine the movements that contributed the most to the overall developmental assessment. RESULTS: Behavioral videos of 4 gross motor skills were collected from 147 children, resulting in a total of 2395 videos. The stage-1 GCN model to evaluate each behavior had an area under the receiver operating characteristic curve (AUROC) of 0.79 to 0.90. Keypoint-mapping Grad-CAM visualization identified important moments in each behavior and differences in important body parts. The stage-2 XGBoost model to assess the overall gross motor status had an AUROC of 0.90. Among the 4 behaviors, "go down the stairs" contributed the most to the overall developmental assessment. CONCLUSIONS: Using movement videos of toddlers aged 18-35 months, we developed objective and automated models to evaluate each behavior and assess each child's overall gross motor performance. We identified the important behaviors for assessing gross motor performance and developed methods to recognize important moments and body parts while evaluating gross motor performance.

Cryo-EM structure of a 16.5-kDa small heat-shock protein from Methanocaldococcus jannaschii.

The small heat-shock protein (sHSP) from the archaea Methanocaldococcus jannaschii, MjsHSP16.5, functions as a broad substrate ATP-independent holding chaperone protecting misfolded proteins from aggregation under stress conditions. This protein is the first sHSP characterized by X-ray crystallography, thereby contributing significantly to our understanding of sHSPs. However, despite numerous studies assessing its functions and structures, the precise arrangement of the N-terminal domains (NTDs) within this sHSP cage remains elusive. Here we present the cryo-electron microscopy (cryo-EM) structure of MjsHSP16.5 at 2.49-Å resolution. The subunits of MjsHSP16.5 in the cryo-EM structure exhibit lesser compaction compared to their counterparts in the crystal structure. This structural feature holds particular significance in relation to the biophysical properties of MjsHSP16.5, suggesting a close resemblance to this sHSP native state. Additionally, our cryo-EM structure unveils the density of residues 24-33 within the NTD of MjsHSP16.5, a feature that typically remains invisible in the majority of its crystal structures. Notably, these residues show a propensity to adopt a ß-strand conformation and engage in antiparallel interactions with strand ß1, both intra- and inter-subunit modes. These structural insights are corroborated by structural predictions, disulfide bond cross-linking studies of Cys-substitution mutants, and protein disaggregation assays. A comprehensive understanding of the structural features of MjsHSP16.5 expectedly holds the potential to inspire a wide range of interdisciplinary applications, owing to the renowned versatility of this sHSP as a nanoscale protein platform.

Deep learning-based natural language processing for detecting medical symptoms and histories in emergency patient triage.

OBJECTIVE: The manual recording of electronic health records (EHRs) by clinicians in the emergency department (ED) is time-consuming and challenging. In light of recent advancements in large language models (LLMs) such as GPT and BERT, this study aimed to design and validate LLMs for automatic clinical diagnoses. The models were designed to identify 12 medical symptoms and 2 patient histories from simulated clinician-patient conversations within 6 primary symptom scenarios in emergency triage rooms. MATERIALS AND METHOD: We developed classification models by fine-tuning BERT, a transformer-based pre-trained model. We subsequently analyzed these models using eXplainable artificial intelligence (XAI) and the Shapley additive explanation (SHAP) method. A Turing test was conducted to ascertain the reliability of the XAI results by comparing them to the outcomes of tasks performed and explained by medical workers. An emergency medicine specialist assessed the results of both XAI and the medical workers. RESULTS: We fine-tuned four pre-trained LLMs and compared their classification performance. The KLUE-RoBERTa-based model demonstrated the highest performance (F1-score: 0.965, AUROC: 0.893) on human-transcribed script data. The XAI results using SHAP showed an average Jaccard similarity of 0.722 when compared with explanations of medical workers for 15 samples. The Turing test results revealed a small 6% gap, with XAI and medical workers receiving the mean scores of 3.327 and 3.52, respectively. CONCLUSION: This paper highlights the potential of LLMs for automatic EHR recording in Korean EDs. The KLUE-RoBERTa-based model demonstrated superior classification performance. Furthermore, XAI using SHAP provided reliable explanations for model outputs. The reliability of these explanations was confirmed by a Turing test.

Time-Resolved Structural Measurement of Thermal Resistance across a Buried Semiconductor Heterostructure Interface.

The precise control and understanding of heat flow in heterostructures is pivotal for advancements in thermoelectric energy conversion, thermal barrier coatings, and efficient heat management in electronic and optoelectronic devices. In this study, we employ high-angular-resolution time-resolved X-ray diffraction to structurally measure thermal resistance in a laser-excited AlGaAs/GaAs semiconductor heterostructure. Our methodology offers femtometer-scale spatial sensitivity and nanosecond time resolution, enabling us to directly observe heat transport across a buried interface. We corroborate established Thermal Boundary Resistance (TBR) values for AlGaAs/GaAs heterostructures and demonstrate that TBR arises from material property discrepancies on either side of a nearly flawless atomic interface. This work not only sheds light on the fundamental mechanisms governing heat flow across buried interfaces but also presents a robust experimental framework that can be extended to other heterostructure systems, paving the way for optimized thermal management in next-generation devices.

Exploring TEM Coherence Properties via Speckle Contrast Analysis in Coherent Electron Scattering of Amorphous Material.

We investigate the coherence properties of a transmission electron microscope by analyzing nano-diffraction speckles originating from bulk metallic glass. The spatial correlation function of the coherent diffraction patterns, obtained in the transmission geometry, reveals the highly coherent nature of the electron probe beam and its spatial dimension incident on the sample. Quantitative agreement between the measured speckle contrast and an analytical model yields estimates for the transverse and longitudinal coherence lengths of the source. We also demonstrate that the coherence can be controlled by changing the beam convergence angle. Our findings underscore the preservation of electron beam coherence throughout the electron optics, as evidenced by the high-contrast speckles observed in the scattering patterns of the amorphous system. This study paves the way for the application of advanced coherent diffraction methodologies to investigate local structures and dynamics occurring at atomic-length scales across a diverse range of materials.

Factors Affecting the Life Satisfaction of School-Aged Children with Vietnamese Immigrant Mothers in Korea.

Low life satisfaction among multicultural children is an important issue related to children's mental health in Korea. The purpose of this study was to identify factors influencing the life satisfaction of children whose Vietnamese mothers migrated to Korea for marriage. Data from the Multicultural Adolescents Panel Study (MAPS) conducted by the National Youth Policy Institute (NYPI) in 2020 were used. The participants were 586 elementary school students. The mean age was 11.01 years (SD 0.19), and 52.0% were girls. Based on Engel's biopsychosocial (BPS) model, biological factors (gender, physical health, and body mass index), psychological factors (mental health, acculturative stress, self-esteem, and general stress), and sociocultural factors (family economic status, social support, and parenting style) were measured and analyzed by using hierarchical multiple regression. In the final model, self-esteem (ß = 0.399, p < 0.001), parental social support (ß = 0.184, p < 0.001), and neglectful parenting style (ß = 0.085, p = 0.031) were positively related to children's life satisfaction, whereas general stress (ß = -0.213, p < 0.001) and acculturative stress (ß = -0.104, p = 0.002) were negatively related. The overall explanatory power was 41.7%. In conclusion, it is necessary to develop a specialized program that focuses on strengthening the bonds between parents and their children to enhance family functioning for multicultural families.

Comprehensive Survey of ChIP-Seq Datasets to Identify Candidate Iron Homeostasis Genes Regulated by Chromatin Modifications.

Vital biochemical reactions including photosynthesis to respiration require iron, which should be tightly regulated. Although increasing evidence reveals the importance of epigenetic regulation in gene expression and signaling, the role of histone modifications and chromatin remodeling in plant iron homeostasis is not well understood. In this study, we surveyed publicly available ChIP-seq datasets of Arabidopsis wild-type and mutants defective in key enzymes of histone modification and chromatin remodeling and compared the deposition of epigenetic marks on loci of genes involved in iron regulation. Based on the analysis, we compiled a comprehensive list of iron homeostasis genes with differential enrichment of various histone modifications. This report will provide a resource for future studies to investigate epigenetic regulatory mechanisms of iron homeostasis in plants.

Arabidopsis thaliana: a powerful model organism to explore histone modifications and their upstream regulations.

Histones are subjected to extensive covalent modifications that affect inter-nucleosomal interactions as well as alter chromatin structure and DNA accessibility. Through switching the corresponding histone modifications, the level of transcription and diverse downstream biological processes can be regulated. Although animal systems are widely used in studying histone modifications, the signalling processes that occur outside the nucleus prior to histone modifications have not been well understood due to the limitations including non viable mutants, partial lethality, and infertility of survivors. Here, we review the benefits of using Arabidopsis thaliana as the model organism to study histone modifications and their upstream regulations. Similarities among histones and key histone modifiers such as the Polycomb group (PcG) and Trithorax group (TrxG) in Drosophila, Human, and Arabidopsis are examined. Furthermore, prolonged cold-induced vernalization system has been well-studied and revealed the relationship between the controllable environment input (duration of vernalization), its chromatin modifications of FLOWERING LOCUS C (FLC), following gene expression, and the corresponding phenotypes. Such evidence suggests that research on Arabidopsis can bring insights into incomplete signalling pathways outside of the histone box, which can be achieved through viable reverse genetic screenings based on the phenotypes instead of direct monitoring of histone modifications among individual mutants. The potential upstream regulators in Arabidopsis can provide cues or directions for animal research based on the similarities between them.

Association of rheumatoid arthritis with bronchial asthma and asthma-related comorbidities: A population-based national surveillance study.

Background: The aim of this study was to investigate the impact of rheumatoid arthritis (RA) on the prevalence of bronchial asthma and asthma-related comorbidities. We also aimed to identify the influence of RA on interrelationship between asthma and asthma-related comorbidities. Methods: From the Korean National Health and Nutrition Examination Survey, participants >40 years of age who completed questionnaires and spirometry tests were enrolled. Patient data on RA, asthma, allergic rhinitis, atopic dermatitis, chronic obstructive pulmonary disease (COPD), sinusitis, otitis media, and body mass index (BMI) were collected. Logistic regression and network analyses were performed. Results: A total of 14,272 subjects were enrolled, among which, 334 (2.4%) had RA. RA was significantly associated with asthma (OR 2.32; 95% CI 1.51-3.57), allergic rhinitis (OR 1.51; 95% CI 1.08-2.10), and sinusitis (OR 1.64; 95% CI 1.08-2.50). The network analysis of total patients revealed a positive interrelationship between asthma and allergic rhinitis, sinusitis, otitis media, atopic dermatitis, BMI, and RA. The interrelationship between asthma and sinusitis was stronger in the RA group. Of note, the relationship between asthma and BMI was distinctively found only in the RA group (r = 0.214, P < 0.05). In patients with asthma, the prevalence of obesity was 64% in the presence of RA, and 40% in the absence of RA (P = 0.034). Conclusion: This study supports the positive association of RA with asthma, allergic rhinitis, and sinusitis. Our analysis suggests a notable interrelationship between the presence of asthma and higher BMI values in patients with RA, indicating that asthma is more obesity-related in patients with RA.

Design, synthesis, and biological evaluation of novel HSP27 inhibitors to sensitize lung cancer cells to clinically available anticancer agents.

Expression of heat shock protein (HSP) correlates with the oncogenic status of malignant cells and plays an important role in tumorigenesis. HSP27 is constitutively expressed at specific stages of cancer development, and several clinical trials have reported correlations between HSP27 expression and tumor progression, metastasis, and chemoresistance in various types of cancer cells. These findings indicate that HSP27 is a major drug target, particularly in chemo-resistant cancers. As part of our ongoing efforts to improve the previously identified J2, a HSP27 cross-linker, we, in this study, report the identification of NK16 as a novel inducer of abnormal HSP27 dimers that did not affect the expression of HSP90 in an NCI-H460 lung cancer cell model. When NCI-H460 cells were treated with NK16 in combination with the anticancer drug cisplatin or paclitaxel, cleavage of PARP and caspase-3 was increased compared to administration of cisplatin or paclitaxel alone. Similar results were obtained in an NCI-H460-xenografted mouse model, in which tumor growth was suppressed more by co-administration of NK16 and paclitaxel than by paclitaxel alone. We propose NK16 as a meaningful strategy to improve the anticancer efficacy of cisplatin and paclitaxel.

BRCA1 deficiency in triple-negative breast cancer: Protein stability as a basis for therapy.

Mutations in breast cancer-associated 1 (BRCA1) increase the lifetime risk of developing breast cancer by up to 51% over the risk of the general population. Many aspects of this multifunctional protein have been revealed, including its essential role in homologous recombination repair, E3 ubiquitin ligase activity, transcriptional regulation, and apoptosis. Although most studies have focused on BRCA1 deficiency due to mutations, only a minority of patients carry BRCA1 mutations. A recent study has suggested an expanded definition of BRCA1 deficiency with reduced BRCA1 levels, which accounts for almost half of all triple-negative breast cancer (TNBC) patients. Reduced BRCA1 levels can result from epigenetic modifications or increased proteasomal degradation. In this review, we discuss how this knowledge of BRCA1 function and regulation of BRCA1 protein stability can help overcome the challenges encountered in the clinic and advance current treatment strategies for BRCA1-related breast cancer patients, especially focusing on TNBC.

Correction: Digital Device Exposure and Cognition Levels of Children in Low- and Middle-Income Countries: Cross-sectional Study in Cambodia.

[This corrects the article DOI: .].

Multi-omics analysis reveals the genetic basis of rice fragrance mediated by betaine aldehyde dehydrogenase 2.

INTRODUCTION: Fragrance is an important economic and quality trait in rice. The trait is controlled by the recessive gene betaine aldehyde dehydrogenase 2 (BADH2) via the production of 2-acetyl-1-pyrroline (2AP). OBJECTIVES: Variation in BADH2 was evaluated at the population, genetic, transcriptional, and metabolic levels to obtain insights into fragrance regulation in rice. METHODS: Whole-genome resequencing of the Korean World Rice Collection of 475 rice accessions, including 421 breeding lines and 54 wild accessions, was performed. Transcriptome analyses of a subset of 279 accessions, proteome analyses of 64 accessions, and volatile profiling of 421 breeding lines were also performed. RESULTS: We identified over 3.1 million high-quality single nucleotide polymorphisms (SNPs) in Korean rice collection. Most SNPs were present in intergenic regions (79%), and 190,148 SNPs (6%) were located in the coding sequence, of which 53% were nonsynonymous. In total, 38 haplotypes were identified in the BADH2 coding region, including four novel haplotypes (one in cultivated and three in wild accessions). Tajima's D values suggested that BADH2 was under balancing selection in japonica rice. Furthermore, we identified 316 expression quantitative trait loci (eQTL), including 185 cis-eQTLs and 131 trans-eQTLs, involved in BADH2 regulation. A protein quantitative trait loci (pQTL) analysis revealed the presence of trans-pQTLs; 13 pQTLs were mapped 1 Mbp from the BADH2 region. Based on variable importance in projection (VIP) scores, 15 volatile compounds, including 2AP, discriminated haplotypes and were potential biomarkers for rice fragrance. CONCLUSION: We generated a catalog of haplotypes based on a resequencing analysis of a large number of rice accessions. eQTLs and pQTLs associated with BADH2 gene expression and protein accumulation are likely involved in the regulation of 2AP variation in fragrant rice. These data improve our understanding of fragrance and provide valuable information for rice breeding.

Correction: Development and Application of a Metaverse-Based Social Skills Training Program for Children With Autism Spectrum Disorder to Improve Social Interaction: Protocol for a Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/35960.].

Minireview: Chromatin-based regulation of iron homeostasis in plants.

Plants utilize delicate mechanisms to effectively respond to changes in the availability of nutrients such as iron. The responses to iron status involve controlling gene expression at multiple levels. The regulation of iron deficiency response by a network of transcriptional regulators has been extensively studied and recent research has shed light on post-translational control of iron homeostasis. Although not as considerably investigated, an increasing number of studies suggest that histone modification and DNA methylation play critical roles during iron deficiency and contribute to fine-tuning iron homeostasis in plants. This review will focus on the current understanding of chromatin-based regulation on iron homeostasis in plants highlighting recent studies in Arabidopsis and rice. Understanding iron homeostasis in plants is vital, as it is not only relevant to fundamental biological questions, but also to agriculture, biofortification, and human health. A comprehensive overview of the effect and mechanism of chromatin-based regulation in response to iron status will ultimately provide critical insights in elucidating the complexities of iron homeostasis and contribute to improving iron nutrition in plants.

High-content phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons using machine learning classification.

Combining multiple Parkinson's disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic neuron (mDAN) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control, and genetically unrelated iPSCs into mDANs. Using automated fluorescence microscopy in 384-well-plate format, we identified elevated levels of α-synuclein (αSyn) and serine 129 phosphorylation, reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDANs according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or αSyn levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient-derived SNCA gene triplication mDAN model which overexpresses αSyn. This phenotyping and classification strategy improves the practical exploitability of mDANs for disease modeling and the identification of novel LRRK2-associated drug targets.

Digital Device Exposure and Cognition Levels of Children in Low- and Middle-Income Countries: Cross-sectional Study in Cambodia.

BACKGROUND: Policy makers and practitioners in low- and middle-income countries (LMICs) are increasingly focusing on the effectiveness of digital devices in the delivery of medical and educational services to children under resource constraints. It is widely known that digital literacy can be fostered through exposure to and education regarding digital devices, which can improve children's academic performance as well as their search and communication skills in the digital era. However, the correlation between the cognitive function of children and exposure and intensity of the exposure to digital devices has rarely been studied, and the association between digital device exposure and the socioeconomic characteristics and cognitive development of children in LMICs is unknown. OBJECTIVE: This study examines the association among exposure to digital devices, socioeconomic status, and cognitive function in children aged 3 to 9 years in Cambodia. METHODS: We used a survey of 232 children that gathered data on familiarity with digital devices, demographic characteristics, and socioeconomic status, as well as a Cambridge Neuropsychological Test Automated Battery test for cognitive function, to examine the association between possible barriers and factors that may influence the cognitive function of children in 2 Cambodian schools from April 22, 2019, to May 4, 2019. A comparative analysis was performed with and without digital exposure, and an association analysis was performed among the variables from the survey and cognitive function. RESULTS: Significant differences were observed in demographic and socioeconomic characteristics such as school location, family type, and family income according to digital device exposure. The results of the Cambridge Neuropsychological Test Automated Battery tests, except for 1 test related to executive function, indicated no significant differences (P>.05) between group A and group B or among the 4 subgroups. Pretest digital device experience and amount of time spent using digital devices during the test had no significant impacts on the cognitive development of the children. Conversely, the multivariate analyses showed that cognitive function was associated with educational expenses per child, school (location), family type, and family income. CONCLUSIONS: These results provide evidence to policy makers and practitioners on the importance of improving socioeconomic conditions, leading to investment in education by implementing programs for children's cognitive development through digital devices in LMICs.

Development and Application of a Metaverse-Based Social Skills Training Program for Children With Autism Spectrum Disorder to Improve Social Interaction: Protocol for a Randomized Controlled Trial.

BACKGROUND: Autism spectrum disorder (ASD) is characterized by abnormalities in social communication and limited and repetitive behavioral patterns. Children with ASD who lack social communication skills will eventually not interact with others and will lack peer relationships when compared to ordinary people. Thus, it is necessary to develop a program to improve social communication abilities using digital technology in people with ASD. OBJECTIVE: We intend to develop and apply a metaverse-based child social skills training program aimed at improving the social interaction abilities of children with ASD aged 7-12 years. We plan to compare and analyze the biometric information collected through wearable devices when applying the metaverse-based social skills training program to evaluate emotional changes in children with ASD in stressful situations. METHODS: This parallel randomized controlled study will be conducted on children aged 7-12 years diagnosed with ASD. A metaverse-based social skills training program using digital technology will be administered to children who voluntarily wish to participate in the research with consent from their legal guardians. The treatment group will participate in the metaverse-based social skills training program developed by this research team once a week for 60 minutes per session for 4 weeks. The control group will not intervene during the experiment. The treatment group will use wearable devices during the experiment to collect real-time biometric information. RESULTS: The study is expected to recruit and enroll participants in March 2022. After registering the participants, the study will be conducted from March 2022 to May 2022. This research will be jointly conducted by Yonsei University and Dobrain Co Ltd. Children participating in the program will use the internet-based platform. CONCLUSIONS: The metaverse-based Program for the Education and Enrichment of Relational Skills (PEERS) will be effective in improving the social skills of children with ASD, similar to the offline PEERS program. The metaverse-based PEERS program offers excellent accessibility and is inexpensive because it can be administered at home; thus, it is expected to be effective in many children with ASD. If a method can be applied to detect children's emotional changes early using biometric information collected through wearable devices, then emotional changes such as anxiety and anger can be alleviated in advance, thus reducing issues in children with ASD. TRIAL REGISTRATION: Clinical Research Information Service KCT0006859; https://tinyurl.com/4r3k7cmj. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/35960.